It’s always inspiring to hear from people who love what they do. Our Data Visualization Studio class was fortunate to welcome three (remote) guest speakers: Luís Melgar, Julia Wolfe and Maarten Lambrechts. I want to share my notes and takeaways both as a reminder for myself and to share with anyone learning more about data visualization like me. Warning: This is a long post.

Luís Melgar: learn something new & a great way to Quiet Imposter Syndrome

What I particularly loved about Luís’s talk was the mix of professional and personal advice. It was positive and endearing, a talk that makes you feel good and ok exactly where you are.

Keep a data journal

Log your data, track your sources to maintain sanity. Truth, this. If you’ve ever felt like you were drowning in data or hunting for sources in the middle or near the end of a project, this is your life jacket.

Write down what you did with the data, how you came up with your conclusions. This is accountability.

Expect the unexpected

Make peace with yourself

Coding is hard. So, for those who aren’t natural coders, it’s OK if you can’t execute what you have in your mind. Luís shared his experience working on his Master’s capstone and some of the hurdles he came across and how he learned to adapt and work around his own limitations.

Know your technical limitations

Different companies and organizations use a wide range of publishing tools. Understand what is possible within those constraints.

Always keep your audience in mind

Make your visualizations responsive and usable on mobile. This is a must.

Don’t ask for too much advice.

This tip made me think of some photographers I know who seem to ask too many people to give them feedback about their work. Let me clarify: I think it is OK to ask as many people as you want but take advice from just a few— the people you trust most. It was nice to hear Luis same the same. Basically everyone has an opinion but whom do you trust?

Love your Classmates

Yes indeed. Luís shared a funny photo of some of his classmates (with some random dude cute out – lol) and how he continues to stay in touch. He shared a couple of memories about music and food which was sweet and funny.

Life is about relationships. The relationships you build or burn in graduate school will have a big impact on your life moving forward. Take the time to learn something new about the people you see every day. They will enrich your life in so many ways.

Keep a notebook of success stories

This. I was surprised to hear him talk about imposter syndrome and it was refreshing to hear someone with so much more experience share that even he suffers from it from time-to-time. He shared how women and minorities tend to experience it more. Interesting.

His solution? Keep a notebook close by where you write down your success stories —what you have learned or accomplished. Big or small. When you are feeling like an imposter, or perhaps just feeling a bit low or unsure, refer to your notebook. It’ll make you feel better; that you are making progress; that you are learning; that you are exactly where you need to be and where you are supposed to be.

Thank you Luís. It was wonderful and inspiring to hear from a graduate of our program.

Knowledge

Understand state laws. What are you legally within right to request and what are institutions required to give you? I loved this tip. I learned state laws and policy is important secondary research for product design, too.

Understand different data formats: PDF? Excel? I took this to also mean, understand how to read them and how to extract data from PDFs (Tabula to the rescue …)

I’m glad he did because he made a story I would probably pass over into a story I wanted to read. Even more, I wished for a follow-up. What more could I learn? For example, when he shared a brief look at his sketches and a sentiment analysis he had done, I wanted to learn more. What patterns are developing in Europe?

Details from Why Budapest, Warsaw, and Lithuania Split Themselves into Two

This is where things start to get interesting.Love this transition and alternate view of looking at the same data.

Honestly, Maarten’s talk was a good inside look at what it takes to be a data journalist/ data visualization designer. It was a bit of a wake up call, too. It takes a certain level of tenacity, a doggedness, if you will. Perhaps this is why I latched on to a quote he made during an interview with Open Belgium 2016:

If you want to become a data journalist, you should start thinking like a programmer.

Maarten Lambrechts

There’s just something about programming that is empowering. Perhaps because it forces you to look at a problem in many different ways. It changes how you think about things, look and interact with the world. Hmm…

Like many other professions, what most people see is the finished, polished work. Viewers/readers don’t see what goes on behind the curtain. That’s what I enjoyed most about Maarten’s talk. He showed us his sketches, his thinking; what worked, what didn’t. It was a comfort to see the mess.

Thank you Maarten for the incredible resources and sharing your story with us. Consider me a new fan of your blog.

Thanks

Wow, you made it to the bottom. Nice.

Thank you data visualization community for your generosity. Ya’ll are icing on the cupcake.

Shirley Wu, one half of the popular Data Sketches project, creates highly interactive, beautiful data visualizations. Here, she gives us a look behind the scenes and shares the lessons she’s learned.

It was an inspiring read. I love stories about people who make changes; that she switched from being a front-end software engineer to become a data visualization designer is cupcake.

So, do you recall periods in your life when you are planning your next step or struggling or hoping for something but not sure what and the universe sends you a person or a moment or a sign to help you take that one small step forward?

This interview with Shirley is one of those moments. Noticing that small cover line near the UPC symbol is nearly impossible but I did and that led me to discovering Beautiful for the first time. Why is this important? Because I’m planning to tackle my first interactive data visualization of poems (Pablo Neruda? Anne Sexton? Maya Angelou? — I need to decide) and it helps to see what other data viz designers have done using text. Part of learning is seeing and understanding what is possible. It may take me some time to reach Shirley’s level of talent but her work and her words were a spark.

Correction: In my excitement, I had flipped Shirley Wu and Nadieh Bremmer’s work in my mind. My sincere apologies to both women. Nadieh is the designer behind Beautiful and Shirley is the designer of Explore Adventure (below), an equally beautiful (see what I did there?) and fun visualization about the travel search connections between countries, seasons, attractions, and more.

Screengrabs from Explore Adventure. This section about searches for Qin Shi Huang was the most interesting; however, I’m trying to still understand how I’m supposed to know the searches happen during spring, summer, winter or fall when just looking at the visualizations.

Lesson learned? Give yourself enough time to triple check your work, what you read, and own up to your mistakes.

The snaking animation is delightful and on hover, I learned more.

What I love about Beautiful is the overall simplicity, the subtle animations and the surprising level of detail and information which isn’t obvious at first. It’s fun and interesting. My only wish: a little more feedback during my interaction with the top 10 words per language.

I wanted a slight animated fade or subtle change in value when I hovered over any of the shapes for each country.

Legends is just stunning and ok, I admit, I have a thing for that color palette. The cool factor is huge. Immediately I wished for Legends to be realized into a physical space that I could walk in and around (VR anyone?) with additional layers of information as I interact with each crystal.

This feels like you are flying just above the surface of an alien planet (I watch a lot of Sci-Fi).I imagined myself walking among these crystals. What if I could touch them and they would light up and reveal something interesting?

I also admire the fact that she shares her knowledge about D3.js with others through workshops (with live coding!), user groups and online courses. She mentions her process and a lot of the tools she uses to clean, understand, explore, prototype, and design. It is a list I’m definitely planning to check out as I begin my journey learning D3.js through Coursera and making my first interactive visualizations.

So, thank you, Shirley Wu for making feel even more excited about data visualization, sharing lessons you’ve learned, your take on tools, and showing me what is possible with D3.js.

I cannot wait to see more of what you create.

PS: It’s always nice to read about people you know, especially when you are also learning from the same. She mentions Alberto twice. The first when he invited her to dive into data that would result in Beautiful and the second when she mentions how teaching forced her to learn so she read a few books. The Functional Art, she says, is “one of my favourites”. Cool.

Professor Cairo has a voracious appetite for reading and he thankfully likes to share books and articles. One article he included, Finding the Best Free Fonts for Numbers was an interesting read as I have a thing for type and fonts. I get picky and can spend probably too much time selecting a font that I feel works well. I’ve also taught typography classes so while I am not a type expert, I am knowledgeable about typography.

In general, I agree with the list Samantha recommends. Not everyone can afford some of the best designed super families out in the wild. I also agree that free fonts aren’t always the best choice. Most are poorly designed and more importantly were probably created for the most generic of applications. So, again, she has compiled a thoughtful list.

Old Standard TT

I do not think it would function well for data visualizations where type sizes are below possibly 14 points and that might be generous. Why? Old Standard TT can be quite interesting at large sizes; however, at smaller sizes, it starts to fall apart.

I need reading glasses to be able to read Old Standard TT at 14 pts. Even with it set in black on a white background (great contrast between figure and ground), it is quite challenging to read. Imagine if it is set in a color also on a colored background. Personally, if it is hard to read, I won’t. In my mind, that is the worst possible user experience.

My recommendation: If you want to use Old Standard TT, use it for display copy—headlines, subheads, or instances where you want to set a numeral in a particularly large size.

Oldstyle or Lining

Samantha’s recommendation for lining and tabular is a good base; however, this should not be a hard and fast rule. Why? Because there is a purpose for Oldstyle figures. Oldstyle figures work well when used with running text. They don’t interrupt the flow of reading because they share the same x-height as their lowercase character companions. Lining numbers in contrast stand out when sharing the same baseline as lowercase characters in running text.

Oldstyle figures can be used for data visualizations especially in places where numbers share the same baseline as text. For example, annotations. They are also readable in tables and other data visualizations purposes. Oldstyle figures can also be tabular so please, don’t rule out a typeface because they have oldstyle figures.

OpenType and Investing in Typefaces

With OpenType fonts, you get the best of all worlds, usually. For figures, OpenType give you the flexibility of setting figures in tabular and lining and tabular and oldstyle. Usually a designer can also set type as proportional as well. This is one of the perks of OpenType fonts and investing in building a library of high-quality typefaces. (Use a font manager such as Extensis’s Suitcase Fusion). Many free fonts are not OpenType.

My Favorite Fonts for Data Visualizations So Far…

Below is a short list of sans serif typefaces I use over and over again. Many are large families so you also have a choice of many styles: thin, light, italic, regular, bold, etc.

If you have an Adobe CC subscription …

Many of the fonts above are available through fonts.adobe.com (formerly TypeKit). It’s one of the perks of having an Adobe Creative Cloud subscription. If you are interested in others, try a search for sans serif with a large x-height. (A larger x-height usually means greater readability at smaller sizes.)

If you want to learn more about typography, I highly recommend Ellen Lupton’s website and book, Thinking with Type. I also have plenty of books which I’ll try to share soon. The great part about owning high-quality typefaces: you don’t need many. This is what makes OpenType super families so appealing.

Early in the semester, Professor Cairo introduced us to Data Illustrator, an open source tool that was designed to create data visualizations and infographics without programming.

My first graphic using Data Illustrator:

This was for a class exercise. I used data already provided by Data Illustrator so I could get a feel for how to use it. I imported it into Adobe Illustrator to clean it up and add copy.

My second graphic using Data Illustrator:

This is a heatmap I made to include in my final project for the Intro to Data Visualization course. I made it in DI and then exported as an SVG to modify using Adobe Illustrator. I love how this turned out.

What I Love and Hate

Love: The seeming flexibility.

Even though I don’t really feel anywhere near comfortable using DI, I can see from the examples that it is very flexible in terms of the type of visualizations that can be created. Plus, I was able to create the heat map above with Data Illustrator which I could not figure out how to do with any other tool in my student tool kit.

Hate: The hurdles of learning its flexibility

I am a beginner with visualization and Data Illustrator but as someone who is learning about user research and user experience, the UX could be greatly improved for novice users. I have no idea how experts in data viz feel about Data Illustrator but from a novice point-of-view the usability — efficiency, effectiveness, and satisfaction — is low.

Love: Downloading the files as SVG

The ability to download SVG files and modify them in Illustrator is very cool. The files are relatively clean (compared to Flourish) and works great.

Hate: Saving projects

Ok, it would be nice if I could save the project name within Data Illustrator rather than having to rename an Untitled DI file after I it downloads to my desktop. This is just so counter-intuitive. Still, at least when you re-open a saved DI file, the web-based tool actually recognizes it and it works so you can continue to modify as desired.

I wish and hope…

A usability test will be done if not already with Data Illustrator to improve it. It think it has a lot of promise but from a usability standpoint, it really needs refinement. Some user testing and UI improvements and improvements to the Help and Documentation especially for novice uses would help make Data Illustrator really shine.

So … where do I start? I love maps! As strange as this may sound, I had forgotten how much I love them. It took an Intro to Data Visualization course to remind me or renew that spark and I’m so glad.

Even with my love for maps, I never really studied them; looked closely or heck, even questioned them. For me, it was about where I had traveled, where I wanted to go, how I would get from point A to point B. I used to be the navigator for my dad when our family would take road trips. I loved having that responsibility; knowing where we are, how we will reach our destination … Big girl stuff.

But I guess with GPS, maps aren’t so much a presence in our daily lives and perhaps that is how I forgot my love of maps?

Learning and looking at maps through a different lens

These are just a few of the maps I’ve been drawn to of late. The first of measles in the United States in 2019. It’s nothing ground-breaking but it sure is astonishing as it is attractive which is an odd thing to say about a map that presents disease.

But, I think that is what is most interesting about being human. What catches our eye can be a twist on the expected? I’m not sure if I’m explaining that well but that’s how it feels for now.

The colors are striking. The reds are a direct link to measles (I have no idea if that was intentional but that’s what it seems to be) and set off against the neutral grays and creams, they pop out.

Having lived in the Pacific Northwest, I’m a bit shocked that there are so many cases in Southern Washington and Portland, Oregon. But then again, maybe not. I’m not sure what the connection is but it would be interesting to investigate more.

This map above scares me but also comforts me in that currently I live in Syracuse, New York (Miami is temporary as far as I know). I worry about my parents who live in the South and this just brings to mind a ton of questions. What are states doing to prepare for this warmth? It is going to have such an impact on daily life. Bandaids here and there are not going to help though it may make people feel better … I’m no expert on what impacts are but the first thing that comes to mind from just reading the news is water and disease. Everything else from there is like a row of dominoes.

Oh but what I also love about the map above is the pairing with the bar graph of income! If I’m reading this correctly, the intensity of the orange bars are connected to the colors of the map, too. Scary and depressing. Will those with less survive? What will we do as a country to help people who don’t have the resources to escape climate change?

This last map … It’s a map of that shows the age of buildings in Lower Manhattan. The project is called Urban Layers. I looked up one building where my husband and I stay when we visit the City and I definitely want to explore this more because I wonder how the building of buildings is connected in terms of where they are located in Manhattan.

One thing I sort of wished for or thought of was when hovering over the different colors or buildings, it would be cool to read more about them, especially the historic buildings. I guess I’m wishing for just a bit more depth! Check it out.

Plans to learn more about Maps

My summer plans include a lot of learning; mainly code such as R and Javascript. Perhaps I can dabble in some mapping tools as well to get my feet wet. I know that for my final year of graduate school a GIS class is planned but in the meantime, I want to study them more. Maybe there’s a way to practice building maps using R? Or perhaps D3.js?